In this paper we report an evaluation of keypoint descrip- tor compression using as little as 16 bits to describe a single keypoint. We use spectral hashing to compress keypoint de- scriptors, and match them using the Hamming distance. By indexing the keypoints in a binary tree, we can quickly rec- ognize keypoints with a very small database, and efficiently insert new keypoints. Our tests using image datasets with perspective distortion show the method to enable fast key- point recognition and image retrieval with a small code size, and point towards potential applications for scalable visual SLAM on mobile phones.